1
|
Bourke M, McInerney-Leo A, Steinberg J, Boughtwood T, Milch V, Ross AL, Ambrosino E, Dalziel K, Franchini F, Huang L, Peters R, Gonzalez FS, Goranitis I. The Cost Effectiveness of Genomic Medicine in Cancer Control: A Systematic Literature Review. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2025; 23:359-393. [PMID: 40172779 PMCID: PMC12053027 DOI: 10.1007/s40258-025-00949-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/19/2025] [Indexed: 04/04/2025]
Abstract
BACKGROUND AND OBJECTIVE Genomic medicine offers an unprecedented opportunity to improve cancer outcomes through prevention, early detection and precision therapy. Health policy makers worldwide are developing strategies to embed genomic medicine in routine cancer care. Successful translation of genomic medicine, however, remains slow. This systematic review aims to identify and synthesise published evidence on the cost effectiveness of genomic medicine in cancer control. The insights could support efforts to accelerate access to cost-effective applications of human genomics. METHODS The study protocol was registered with PROSPERO (CRD42024480842), and the review was conducted in line with Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) Guidelines. The search was run in four databases: MEDLINE, Embase, CINAHL and EconLit. Full economic evaluations of genomic technologies at any stage of cancer care, and published after 2018 and in English, were included for data extraction. RESULTS The review identified 137 articles that met the inclusion criteria. Most economic evaluations focused on the prevention and early detection stage (n = 44; 32%), the treatment stage (n = 36; 26%), and managing relapsed, refractory or progressive disease (n = 51, 37%). Convergent cost-effectiveness evidence was identified for the prevention and early detection of breast and ovarian cancer, and for colorectal and endometrial cancers. For cancer treatment, the use of genomic testing for guiding therapy was highly likely to be cost effective for breast and blood cancers. Studies reported that genomic medicine was cost effective for advanced and metastatic non-small cell lung cancer. There was insufficient or mixed evidence regarding the cost effectiveness of genomic medicine in the management of other cancers. CONCLUSIONS This review mapped out the cost-effectiveness evidence of genomic medicine across the cancer care continuum. Gaps in the literature mean that potentially cost-effective uses of genomic medicine in cancer control, for example rare cancers or cancers of unknown primary, may be being overlooked. Evidence on the value of information and budget impact are critical, and advancements in methods to include distributional effects, system capacity and consumer preferences will be valuable. Expanding the current cost-effectiveness evidence base is essential to enable the sustainable and equitable translation of genomic medicine.
Collapse
Affiliation(s)
- Mackenzie Bourke
- Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Melbourne, VIC, 3053, Australia
| | - Aideen McInerney-Leo
- Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, QLD, Australia
| | - Julia Steinberg
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia
| | - Tiffany Boughtwood
- Australian Genomics, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Vivienne Milch
- Cancer Australia, Sydney, NSW, Australia
- Caring Futures Institute, Flinders University, Adelaide, SA, Australia
| | - Anna Laura Ross
- Science Division, World Health Organization, Geneva, Switzerland
| | - Elena Ambrosino
- Science Division, World Health Organization, Geneva, Switzerland
| | - Kim Dalziel
- Child Health Economics Unit, School of Population and Global Health, Centre for Health Policy, University of Melbourne, MelbourneMelbourne, VIC, Australia
| | - Fanny Franchini
- Faculty of Medicine, Dentistry and Health Sciences, Cancer Health Services Research, Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
- Department of Cancer Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Li Huang
- Child Health Economics Unit, School of Population and Global Health, Centre for Health Policy, University of Melbourne, MelbourneMelbourne, VIC, Australia
| | - Riccarda Peters
- Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Melbourne, VIC, 3053, Australia
| | - Francisco Santos Gonzalez
- Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Melbourne, VIC, 3053, Australia
| | - Ilias Goranitis
- Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Melbourne, VIC, 3053, Australia.
- Australian Genomics, Murdoch Children's Research Institute, Melbourne, VIC, Australia.
| |
Collapse
|
2
|
Santos Gonzalez F, Ungar WJ, Buchanan J, Christodoulou J, Stark Z, Goranitis I. Microcosting genomics: Challenges and opportunities. Genet Med 2025; 27:101310. [PMID: 39522058 DOI: 10.1016/j.gim.2024.101310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 10/29/2024] [Accepted: 10/29/2024] [Indexed: 11/16/2024] Open
Affiliation(s)
- Francisco Santos Gonzalez
- Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Melbourne, VIC, Australia; Murdoch Children's Research Institute, VIC, Australia
| | - Wendy J Ungar
- Program of Child Health Evaluative Sciences, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, ON, Canada; Institute of Health Policy, Management and Evaluation, The University of Toronto, Toronto, ON, Canada
| | - James Buchanan
- Health Economics and Policy Research Unit, Centre for Evaluation and Methods, Wolfson Institute of Population Health, Queen Mary University of London, Yvonne Carter Building, London, United Kingdom; National Institute for Health Research, Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom
| | - John Christodoulou
- Murdoch Children's Research Institute, VIC, Australia; Australian Genomics, Melbourne, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Zornitza Stark
- Australian Genomics, Melbourne, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Ilias Goranitis
- Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Melbourne, VIC, Australia; Murdoch Children's Research Institute, VIC, Australia; Institute of Health Policy, Management and Evaluation, The University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
3
|
Wildin RS. Cost Effectiveness of Genomic Population Health Screening in Adults: A Review of Modeling Studies and Future Directions. J Appl Lab Med 2024; 9:92-103. [PMID: 38167759 DOI: 10.1093/jalm/jfad093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/09/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Detecting actionable health risks for genetic diseases prior to symptomatic presentation at population scale using genomic test technologies is a preventive health innovation being piloted in multiple locations. Standard practice is to screen for risks only in those with personal or family history of specific disease. Genomic population heath screening has proven feasible and potentially scalable. The value of this intervention in terms of economic benefit has been scientifically modeled by several groups. CONTENT Eight recent cost-effectiveness modeling studies for high penetrance monogenic dominant diseases that used input parameters from 3 different countries are reviewed. Results and their uses in refining implementations are analyzed and the roles for laboratory medicine in facilitating success are discussed. SUMMARY The reviewed studies generally found evidence for cost-effectiveness of genomic population health screening in at least a subset of their base case screening scenario. Sensitivity analyses identified opportunities for improving the likelihood of cost-effectiveness. On the whole, the modeling results suggest genomic population health screening is likely to be cost-effective for high penetrance disorders in younger adults, especially with achievable reductions in test cost effected partially through combining tests for individual disorders into one screening procedure. Policies founded on the models studied should consider limitations of the modeling methods and the potential for impacts on equity and access in the design and implementation of genomic screening programs.
Collapse
Affiliation(s)
- Robert S Wildin
- Departments of Pathology & Laboratory Medicine and Pediatrics, The Larner College of Medicine at the University of Vermont, Burlington, VT, United States
| |
Collapse
|
4
|
Ferket BS, Baldwin Z, Murali P, Pai A, Mittendorf KF, Russell HV, Chen F, Lynch FL, Lich KH, Hindorff LA, Savich R, Slavotinek A, Smith HS, Gelb BD, Veenstra DL. Cost-effectiveness frameworks for comparing genome and exome sequencing versus conventional diagnostic pathways: A scoping review and recommended methods. Genet Med 2022; 24:2014-2027. [PMID: 35833928 PMCID: PMC9997042 DOI: 10.1016/j.gim.2022.06.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/13/2022] [Accepted: 06/15/2022] [Indexed: 01/21/2023] Open
Abstract
PURPOSE Methodological challenges have limited economic evaluations of genome sequencing (GS) and exome sequencing (ES). Our objective was to develop conceptual frameworks for model-based cost-effectiveness analyses (CEAs) of diagnostic GS/ES. METHODS We conducted a scoping review of economic analyses to develop and iterate with experts a set of conceptual CEA frameworks for GS/ES for prenatal testing, early diagnosis in pediatrics, diagnosis of delayed-onset disorders in pediatrics, genetic testing in cancer, screening of newborns, and general population screening. RESULTS Reflecting on 57 studies meeting inclusion criteria, we recommend the following considerations for each clinical scenario. For prenatal testing, performing comparative analyses of costs of ES strategies and postpartum care, as well as genetic diagnoses and pregnancy outcomes. For early diagnosis in pediatrics, modeling quality-adjusted life years (QALYs) and costs over ≥20 years for rapid turnaround GS/ES. For hereditary cancer syndrome testing, modeling cumulative costs and QALYs for the individual tested and first/second/third-degree relatives. For tumor profiling, not restricting to treatment uptake or response and including QALYs and costs of downstream outcomes. For screening, modeling lifetime costs and QALYs and considering consequences of low penetrance and GS/ES reanalysis. CONCLUSION Our frameworks can guide the design of model-based CEAs and ultimately foster robust evidence for the economic value of GS/ES.
Collapse
Affiliation(s)
- Bart S Ferket
- Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY.
| | - Zach Baldwin
- The Comparative Health Outcomes, Policy and Economics (CHOICE) Institute, School of Pharmacy, University of Washington, Seattle, WA
| | - Priyanka Murali
- Division of Medical Genetics, Department of Medicine, University of Washington Medical Center, University of Washington, Seattle, WA
| | - Akila Pai
- Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Kathleen F Mittendorf
- Department of Translational and Applied Genomics (TAG), Kaiser Permanente Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon; Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Heidi V Russell
- Texas Children's Cancer Center, Baylor College of Medicine, Houston, TX; Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX
| | - Flavia Chen
- Program in Bioethics, University of California San Francisco, San Francisco, CA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA
| | | | - Kristen Hassmiller Lich
- Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Lucia A Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Renate Savich
- Department of Pediatrics, University of Mississippi Medical Center, Jackson, MS; Division of Neonatology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM
| | - Anne Slavotinek
- Department of Pediatrics, University of California San Francisco, San Francisco, CA
| | - Hadley Stevens Smith
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX
| | - Bruce D Gelb
- Departments of Pediatrics and Genetics & Genomic Sciences, Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - David L Veenstra
- The Comparative Health Outcomes, Policy and Economics (CHOICE) Institute, School of Pharmacy, University of Washington, Seattle, WA
| |
Collapse
|
5
|
Bick D, Ahmed A, Deen D, Ferlini A, Garnier N, Kasperaviciute D, Leblond M, Pichini A, Rendon A, Satija A, Tuff-Lacey A, Scott RH. Newborn Screening by Genomic Sequencing: Opportunities and Challenges. Int J Neonatal Screen 2022; 8:40. [PMID: 35892470 PMCID: PMC9326745 DOI: 10.3390/ijns8030040] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/09/2022] [Accepted: 07/11/2022] [Indexed: 12/11/2022] Open
Abstract
Newborn screening for treatable disorders is one of the great public health success stories of the twentieth century worldwide. This commentary examines the potential use of a new technology, next generation sequencing, in newborn screening through the lens of the Wilson and Jungner criteria. Each of the ten criteria are examined to show how they might be applied by programmes using genomic sequencing as a screening tool. While there are obvious advantages to a method that can examine all disease-causing genes in a single assay at an ever-diminishing cost, implementation of genomic sequencing at scale presents numerous challenges, some which are intrinsic to screening for rare disease and some specifically linked to genomics-led screening. In addition to questions specific to routine screening considerations, the ethical, communication, data management, legal, and social implications of genomic screening programmes require consideration.
Collapse
Affiliation(s)
- David Bick
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Arzoo Ahmed
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Dasha Deen
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Alessandra Ferlini
- Medical Genetics Unit, Department of Medical Sciences, University of Ferrara, 44121 Ferrara, Italy;
| | | | - Dalia Kasperaviciute
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Mathilde Leblond
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Amanda Pichini
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Augusto Rendon
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Aditi Satija
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Alice Tuff-Lacey
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| | - Richard H. Scott
- Genomics England Ltd., Dawson Hall, Charterhouse Square, Barbican, London EC1M 6BQ, UK; (A.A.); (D.D.); (D.K.); (M.L.); (A.P.); (A.R.); (A.S.); (A.T.-L.); (R.H.S.)
| |
Collapse
|